Mosaic Smart Data and ESA Business Applications is looking to apply its machine-learning models used in space systems to financial markets.
The European Space Agency’s (ESA) commercial arm has announced an alliance to advance the data analytics tools available to banks in the fixed income, currencies and commodities (FICC) markets.
Through the collaboration between the space exploration and FinTech industries, the project will focus on data models used to identify patterns and correlations that are used by ESA for investigating anomalies of deep space satellite missions.
Matthew Hodgson, CEO of Mosaic Smart Data, said: “From fighting climate change to improving financial market surveillance, data analytics technology has the potential to radically reshape the way we approach challenges in many different industries. Through this collaboration we have an incredible opportunity to apply some of the world’s most advanced data analytics models to the problems our clients face in financial markets. Not only that, but we will also be sharing the results of this project with the European Space Agency to help advance their analytics development. Our aim is to positively contribute back to the wider community.”
In financial markets, this technology could be used to automatically identify and create hedging strategy recommendations, as well as giving sales and trading teams a much better indication of the market factors impacting their performance.
These models may also have applications in market surveillance by quickly identifying and flagging suspect trades and behaviour which may subtly fall outside a trader’s typical behaviour patterns.
Mosaic said it will complete a joint-funded feasibility study to explore how ESA’s machine learning technology can benefit financial market participants. If successful, the technology will be built into Mosaic’s suite of analytics models.
With a wave of regulations threatening to plunge the financial services industry into chaos, technologies like AI and ML are promising to ease the burden on compliance officers and ensure firms are meeting regulations.
“The ability to learn from doing and harnessing the data, and the knowledge and process of others will mean that we can mass scale the intellectual property and experience within the entire ecosystem,” according to Donat.
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